Next Generation Resource Discovery linking Geophysical Sensing, Modelling and Interpretation. Issue 1 (1st December 2016)

• Record Type: Journal Article
• Authors: Regenauer-Lieb, Klaus; Poulet, Thomas; Veveakis, Manolis
• Is Part Of: ASEG Extended Abstracts (Online). Volume 2016:Issue 1(2016)
• Page Start: 1
• Page End: 5
• Publication Date: 2016-12-01
• Subjects: Physics-based modelling -- multiscale -- multiphysics -- data assimilation; Prospecting -- Geophysical methods -- Periodicals; Prospecting -- Geophysical methods; Periodicals
• DOI: 10.1071/ASEG2016ab101
• Languages: English
• ISSNs: 2202-0586

Abstract

Abstract : We present a status report on the next generation data assimilation techniques for Resource Discovery using a new multidisciplinary fundamental science approach. We combine a recent multiphysics, multiscale geodynamic theory with laboratory and modern computational assisted petrophysics and material science concepts with the aim of linking it "on the fly" to geological and geophysical field data acquisition. This solid science base is designed to build the platform for enabling a data intensive paradigm for the resource industry. Such a physics-based big data interpretation opportunity has not yet been exploited in current geoscience applications. In other disciplines the approach is, however, fully realized. Owing to its major impact it has been hailed by the US National Research Council [ICME, 2008] as a transformational discipline for improved competitiveness and national security. The approach has been pioneered in polymer sciences, the automotive and aerospace engineering as well as in computational biomechanics, via a so-called "Integrated Computational Materials Engineering" (ICME) cyber-infrastructure. An ICME system unifies materials information into a multi-scale system that is linked by means of software integration tools to a designer knowledge base containing tools and models from different scales and different disciplines.